Transpiration of fraud detection rules to native language source code

Abstract

Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The generated rules with distinct data paths are then converted using a transpiler from the scripting language into native language source code (e.g., PHP, Java, etc.) for deployment in a particular environment. The rules are then executed in real-time in the environment to detect potential fraudulent activity.

What is claimed is: 
     
       1. A fraud detection system comprising:
 a database; and 
 a server connected to the database, the server including a processing unit and a memory, the server configured to:
 generate a first fraud detection rule using a conditional scripting language, the first fraud detection rule including an Anchor attribute and an Add-On identifier, the Anchor attribute and the Add-On identifier corresponding to a first data path for retrieval of a first value related to the Add-On identifier, 
 generate an abstract syntax tree based on the first fraud detection rule, wherein the abstract syntax tree includes a dependency between the first data path and a second data path included in a second fraud detection rule for retrieval of a second value, 
 transpile the first fraud detection rule from the conditional scripting language to a native language source code, 
 store the transpiled first fraud detection rule in the database, the transpiled first fraud detection rule including the first data path for retrieval of the first value related to the Add-On identifier, 
 retrieve the transpiled first fraud detection rule from the database, 
 based on the dependency included in the abstract syntax tree, determine that the second value depends on the first value and prioritize retrieval of the first value related to the Add-On identifier over retrieval of the second value, 
 using the first data path, retrieve the first value related to the Add-On identifier, and 
 utilizing the retrieved first value, execute the transpiled first fraud detection rule in an environment configured to execute fraud rules in the native language source code. 
 
 
     
     
       2. The fraud detection system of  claim 1 , wherein the server is further configured to:
 parse the first fraud detection rule in the conditional scripting language. 
 
     
     
       3. The fraud detection system of  claim 1 , wherein the server is further configured to: validate the first fraud detection rule using the abstract syntax tree. 
     
     
       4. The fraud detection system of  claim 1 , wherein the server is further configured to: validate the transpiled first fraud detection rule for the native language source code. 
     
     
       5. The fraud detection system of  claim 1 , wherein a level of abstraction for the conditional scripting language and a level of abstraction for the native language source code are the same. 
     
     
       6. The fraud detection system of  claim 1 , wherein
 the Anchor attribute corresponds to a first token; and 
 the Add-On identifier corresponds to a second token. 
 
     
     
       7. The fraud detection system of  claim 6 , wherein the first data path is a dot-separated, alphanumeric string that includes the first token and the second token. 
     
     
       8. The fraud detection system of  claim 1 , wherein the native language source code is PHP: Hypertext Preprocessor code. 
     
     
       9. A computer-implemented fraud detection method, the method comprising:
 generating a first fraud detection rule using a conditional scripting language, the first fraud detection rule including an Anchor attribute and an Add-On identifier, the Anchor attribute and the Add-On identifier corresponding to a data path for retrieval of a first value related to the Add-On identifier; 
 generating an abstract syntax tree based on the first fraud detection rule, wherein the abstract syntax tree includes a dependency between the first data path and a second data path included in a second fraud detection rule for retrieval of a second value; 
 transpiling the first fraud detection rule from the conditional scripting language to a native language source code; 
 storing the transpiled first fraud detection rule, the transpiled first fraud detection rule including the data path for retrieval of the first value related to the Add-On identifier; 
 retrieving the transpiled first fraud detection rule; 
 based on the dependency included in the abstract syntax tree, determining that the second value depends on the first value and prioritizing retrieval of the first value related to the Add-On identifier over retrieval of the second value, 
 using the data path, retrieve the first value related to the Add-On identifier; and 
 utilizing the retrieved first value, executing the transpiled first fraud detection rule in an environment configured to execute fraud rules in the native language source code. 
 
     
     
       10. The method of  claim 9 , further comprising:
 parsing the first fraud detection rule in the conditional scripting language. 
 
     
     
       11. The method of  claim 9 , further comprising:
 validating the first fraud detection rule using the abstract syntax tree. 
 
     
     
       12. The method of  claim 9 , wherein a level of abstraction for the conditional scripting language and a level of abstraction for the native language source code are the same. 
     
     
       13. The method of  claim 9 , wherein the native language source code is PHP: Hypertext Preprocessor code. 
     
     
       14. A non-transitory computer readable medium including computer executable instructions stored in the computer readable medium for controlling a device to:
 generate a first fraud detection rule using a conditional scripting language, the first fraud detection rule including an Anchor attribute and an Add-On identifier, the Anchor attribute and the Add-On identifier corresponding to a data path for retrieval of a first value related to the Add-On identifier; 
 generate an abstract syntax tree based on the first fraud detection rule, wherein the abstract syntax tree includes a dependency between the first data path and a second data path included in a second fraud detection rule for retrieval of a second value; 
 transpile the first fraud detection rule from the conditional scripting language to a native language source code; 
 store the transpiled first fraud detection rule, the transpiled first fraud detection rule including the data path for retrieval of the first value related to the Add-On identifier; 
 retrieve the transpiled first fraud detection rule; 
 based on the dependency included in the abstract syntax tree, determine that the second value depends on the first value and prioritize retrieval of the first value related to the Add-On identifier over retrieval of the second value; 
 using the data path, retrieve the first value related to the Add-On identifier, and 
 utilizing the retrieved first value, execute the transpiled first fraud detection rule in an environment-configured to execute fraud rules in the native language source code. 
 
     
     
       15. The non-transitory computer readable medium of  claim 14 , further including computer executable instructions stored in the computer readable medium for controlling the device to:
 parse the first fraud detection rule in the conditional scripting language. 
 
     
     
       16. The non-transitory computer readable medium of  claim 14 , further including computer executable instructions stored in the computer readable medium for controlling the device to:
 validate the first fraud detection rule using the abstract syntax tree. 
 
     
     
       17. The non-transitory computer readable medium of  claim 14 , wherein the native language source code is PHP: Hypertext Preprocessor code.